Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for execution by a dispersed storage network (DSN) monitoring unit that includes a processor, the method comprises: receiving user input via an interface of the DSN monitoring unit, wherein the user input includes configuration parameters that include statistics collection parameters, and wherein the statistics collection parameters indicate a selected plurality of statistics to collect based on the user input; generating a configuration update request for transmission, via a network, to a plurality of managing units based on the configuration parameters, wherein each the plurality of managing units transmit, via the network, a plurality of update specifications to a plurality of storage units managed by the each of the plurality of managing units in response to receiving the configuration update request, wherein the plurality of storage units are separate from the plurality of managing units, and wherein the plurality of managing units apply configuration specifications of the configuration update request to themselves in response to receiving the configuration update request; generating a statistics collection request for transmission, via the network, to the plurality of managing units based on the statistics collection parameters, wherein each the plurality of managing units transmit, via the network, a plurality of statistics collection requests to the plurality of storage units managed by the each of the plurality of managing units in response to receiving the statistics collection request; receiving, in response to the statistics collection request, collected storage unit data from each of the plurality of managing units that includes data collected by the each of the plurality of managing units, via the network, from the plurality of storage units managed by the each of the plurality of managing units, wherein the collected storage unit data received from each of the plurality of managing units corresponds to the selected plurality of statistics of the statistics collection parameters of the user input; and generating aggregated storage statistics based on the collected storage unit data received from each of the plurality of managing units.
2. The method of claim 1 , wherein the configuration parameters indicate at least one configuration setting of at least one dispersed storage component for update by the at least one dispersed storage component, wherein the at least one dispersed storage component includes the plurality of storage units and further includes at least one of: a computing device, a DSN managing unit, or a DSN integrity unit.
This invention relates to distributed storage systems, specifically methods for updating configuration parameters in a dispersed storage network (DSN). The problem addressed is the need to dynamically adjust configuration settings across multiple dispersed storage components to optimize performance, reliability, or other operational aspects of the storage system. The method involves receiving configuration parameters that specify which settings of which storage components should be updated. The storage components include storage units, computing devices, DSN managing units, or DSN integrity units. These parameters define the specific configuration settings to be modified and the components responsible for applying those changes. The method ensures that the updates are applied by the appropriate components, allowing for flexible and targeted adjustments to the system's configuration without requiring centralized control. By enabling individual storage components to update their own settings based on received parameters, the system can adapt to changing conditions, such as load balancing, fault tolerance, or performance optimization, while maintaining decentralized control. This approach improves scalability and resilience in distributed storage environments.
3. The method of claim 1 , wherein the collected storage unit data is received from a proper subset of the plurality of storage units managed by the each of the plurality of managing units, and wherein the proper subset is based on the configuration update request.
This invention relates to distributed storage systems, specifically methods for managing and updating configurations across multiple storage units. The problem addressed is efficiently handling configuration updates in large-scale storage environments where multiple managing units oversee numerous storage units, ensuring updates are applied only to relevant subsets of storage units based on specific requests. The method involves receiving a configuration update request that specifies a subset of storage units to be updated. A managing unit processes this request and identifies the proper subset of storage units from the plurality of storage units it manages, where the subset is determined by the request's criteria. The managing unit then collects data from only these identified storage units, ensuring updates are applied selectively rather than across all storage units. This selective approach optimizes resource usage and reduces unnecessary processing overhead. The method also includes verifying the collected data to ensure consistency and correctness before applying the configuration update. If inconsistencies are detected, the system may trigger corrective actions or notify administrators. This ensures that only valid and relevant updates are propagated, maintaining system reliability. By dynamically determining the subset of storage units based on the update request, the method improves efficiency in distributed storage management, particularly in environments with large numbers of storage units and managing units. This approach minimizes unnecessary data collection and processing, enhancing overall system performance.
4. The method of claim 3 , wherein the data collected from the proper subset of the plurality of storage units includes at least one of statistics or logs corresponding to the proper subset of the plurality of storage units.
This invention relates to data collection and monitoring in storage systems, specifically addressing the challenge of efficiently gathering and analyzing performance data from a subset of storage units within a larger storage system. The system includes a plurality of storage units, where data is collected from a proper subset of these units rather than all of them. The collected data includes at least one of statistics or logs corresponding to the proper subset of storage units. The proper subset is determined based on predefined criteria, such as performance thresholds, error rates, or other operational metrics, ensuring that only relevant storage units are monitored. The collected data is then processed to generate insights, such as performance trends, failure predictions, or optimization recommendations. This selective data collection reduces computational overhead and improves efficiency by focusing on the most critical storage units. The system may also include mechanisms for dynamically adjusting the subset of monitored units based on real-time conditions, ensuring continuous optimization of data collection efforts. The invention is particularly useful in large-scale storage environments where comprehensive monitoring of all units would be resource-intensive.
5. The method of claim 1 , wherein the statistics collection parameters further indicate a selected time frame for statistics collection based on the user input.
A system and method for collecting and analyzing statistics in a computing environment, particularly for monitoring performance metrics of software applications or hardware components. The invention addresses the challenge of efficiently gathering relevant statistical data while minimizing resource overhead and ensuring the data is collected in a manner that aligns with user-defined requirements. The method involves configuring statistics collection parameters based on user input, where these parameters define the specific metrics to be monitored, the frequency of data collection, and the conditions under which data should be recorded. A key aspect of the invention is the ability to specify a selected time frame for statistics collection, allowing users to define the duration or specific intervals during which data should be gathered. This ensures that statistics are collected only when necessary, reducing unnecessary processing and storage demands. The system dynamically adjusts the collection process according to the user-defined parameters, ensuring that the collected data is both relevant and timely. The method may also include filtering or aggregating the collected data to provide meaningful insights while minimizing the volume of stored information. This approach enhances system performance monitoring by providing targeted, user-specific statistical data that can be used for troubleshooting, optimization, or performance analysis. The invention is particularly useful in environments where resource efficiency and precise data collection are critical, such as cloud computing, enterprise software, or embedded systems.
6. The method of claim 1 , wherein the collected storage unit data is received from each of the plurality of managing units as an aggregated report, wherein data provided in the aggregated report is based on the configuration update request.
This invention relates to data management in storage systems, specifically improving the efficiency of collecting and processing storage unit data across multiple managing units. The problem addressed is the inefficiency and complexity of gathering detailed storage unit data from distributed managing units, particularly when configuration updates are requested. Traditional systems often require individual queries to each managing unit, leading to excessive network traffic and processing overhead. The invention provides a method for receiving aggregated reports from each managing unit, where the data in these reports is tailored to a specific configuration update request. Instead of querying each unit separately, the managing units compile and send a consolidated report containing only the relevant data needed for the update. This reduces the volume of data transmitted and processed, improving system performance. The aggregated reports are generated based on the configuration update request, ensuring that only necessary information is collected, minimizing resource usage. This approach streamlines data management in distributed storage environments, making configuration updates faster and more efficient. The method is particularly useful in large-scale storage systems where managing unit data must be frequently updated or monitored.
7. The method of claim 1 , further comprising: generating new configuration parameters, wherein the new configuration parameters are based on the aggregated storage statistics; and generating a new configuration update request for transmission to at least one of the plurality of managing units based on the new configuration parameters.
This invention relates to a system for dynamically adjusting storage configurations in a distributed storage environment. The problem addressed is the inefficiency of static storage configurations, which fail to adapt to changing workloads and resource demands, leading to suboptimal performance and resource utilization. The system monitors storage performance by collecting and aggregating storage statistics from multiple storage units. These statistics include metrics such as read/write latency, throughput, and capacity utilization. The aggregated data is analyzed to identify performance bottlenecks or inefficiencies in the current storage configuration. Based on the analysis, new configuration parameters are generated to optimize storage performance. These parameters may include adjustments to data distribution, caching policies, or resource allocation. The system then generates a configuration update request containing the new parameters and transmits it to one or more managing units responsible for enforcing the changes. The managing units apply the updated configuration to the storage system, dynamically reconfiguring it to improve performance and resource utilization. This adaptive approach ensures that the storage system remains efficient under varying workload conditions. The invention enhances scalability and reliability by continuously optimizing storage configurations in response to real-time data.
8. The method of claim 1 , further comprising storing the collected storage unit data in a memory coupled to the DSN monitoring unit, and wherein generating the aggregated storage statistics is further based on a plurality of past collected storage unit data stored in the memory.
A distributed storage network (DSN) monitoring system collects and analyzes performance data from multiple storage units to generate aggregated statistics. The system addresses the challenge of monitoring and optimizing storage performance across a distributed network by gathering real-time and historical data from storage units. The collected data includes metrics such as read/write speeds, latency, and error rates. This data is stored in a memory coupled to the DSN monitoring unit, allowing the system to analyze both current and past performance trends. By incorporating historical data, the system generates more accurate and comprehensive aggregated statistics, which can be used to identify performance bottlenecks, predict failures, and optimize storage resource allocation. The monitoring system ensures reliable and efficient operation of the distributed storage network by leveraging both real-time and historical performance metrics.
9. The method of claim 1 , further comprising generating projected storage data indicating when future storage will be needed based on the collected storage unit data.
A system and method for managing storage resources in a data storage environment addresses the challenge of efficiently allocating and forecasting storage needs to prevent capacity shortages. The system collects data from storage units, including current usage, performance metrics, and historical trends. This data is analyzed to generate insights into storage utilization patterns and potential future requirements. The method further includes generating projected storage data, which predicts when additional storage capacity will be needed based on the collected storage unit data. By analyzing historical usage trends and current performance, the system forecasts future storage demands, allowing administrators to proactively allocate resources and avoid capacity-related disruptions. The projections may account for factors such as growth rates, seasonal variations, and system performance degradation. This enables organizations to optimize storage allocation, reduce costs, and ensure uninterrupted operations by anticipating and addressing storage needs before they become critical. The system may also integrate with existing storage management tools to provide actionable recommendations for capacity planning and resource optimization.
10. The method of claim 1 , further comprising generating defect signatures data by searching for defect signatures in the collected storage unit data.
This invention relates to data storage systems and methods for detecting and analyzing defects in storage units. The problem addressed is the need for efficient and accurate identification of defects in storage units to ensure data integrity and system reliability. The method involves collecting data from storage units, which may include error logs, performance metrics, and other diagnostic information. This collected data is then analyzed to identify patterns or anomalies indicative of defects. The method further includes generating defect signatures data by searching for specific defect signatures within the collected storage unit data. These defect signatures are unique patterns or markers that correspond to known or potential defects in the storage units. By identifying these signatures, the system can predict, diagnose, or mitigate storage unit failures before they impact data integrity or system performance. The method may also involve comparing the collected data against a database of known defect signatures to determine the type and severity of defects. Additionally, the system may generate alerts or recommendations based on the identified defects, allowing for proactive maintenance or corrective actions. The overall goal is to enhance the reliability and longevity of storage units by detecting defects early and providing actionable insights for system administrators.
11. A processing system of a dispersed storage network (DSN) monitoring unit comprises: at least one processor; a memory that stores operational instructions, that when executed by the at least one processor cause the processing system to: receive user input via an interface of the DSN monitoring unit, wherein the user input includes configuration parameters that include statistics collection parameters, and wherein the statistics collection parameters indicate a selected plurality of statistics to collect based on the user input; generate a configuration update request for transmission, via a network, to a plurality of managing units based on the configuration parameters, wherein each the plurality of managing units transmit, via the network, a plurality of update specifications to a plurality of storage units managed by the each of the plurality of managing units in response to receiving the configuration update request, wherein the plurality of storage units are separate from the plurality of managing units, and wherein the plurality of managing units apply configuration specifications of the configuration update request to themselves in response to receiving the configuration update request; generate a statistics collection request for transmission, via the network, to the plurality of managing units based on the statistics collection parameters, wherein each the plurality of managing units transmit, via the network, a plurality of statistics collection requests to the plurality of storage units managed by the each of the plurality of managing units in response to receiving the statistics collection request; receive, in response to the statistics collection request, collected storage unit data from each of the plurality of managing units that includes data collected by the each of the plurality of managing units, via the network, from the plurality of storage units managed by the each of the plurality of managing units, wherein the collected storage unit data received from each of the plurality of managing units corresponds to the selected plurality of statistics of the statistics collection parameters of the user input; and generate aggregated storage statistics based on the collected storage unit data received from each of the plurality of managing units.
A processing system in a dispersed storage network (DSN) monitoring unit collects and aggregates storage statistics from multiple storage units. The system includes a processor and memory storing instructions to receive user input specifying configuration parameters, including statistics collection parameters that define which statistics to gather. The system generates a configuration update request sent to managing units, which then distribute update specifications to their respective storage units and apply the configurations themselves. The system also generates a statistics collection request sent to the managing units, which forward collection requests to their storage units. The managing units gather data from the storage units and return it to the monitoring unit. The monitoring unit aggregates this data to produce comprehensive storage statistics based on the user-defined parameters. This approach enables centralized monitoring and analysis of storage performance and health across distributed storage units managed by separate managing units.
12. The processing system of claim 11 , wherein the collected storage unit data is received from a proper subset of the plurality of storage units managed by the each of the plurality of managing units, and wherein the proper subset is based on the configuration update request.
This invention relates to a distributed storage system where multiple managing units oversee a plurality of storage units. The system addresses the challenge of efficiently managing and updating configurations across a distributed storage environment. Each managing unit collects data from a proper subset of the storage units it manages, where the subset is determined by a configuration update request. This selective data collection allows for targeted updates and optimizes resource usage by avoiding unnecessary data retrieval from all storage units. The system ensures that only relevant storage units are queried, reducing overhead and improving performance. The managing units process the collected data to apply configuration changes, ensuring consistency and reliability across the distributed storage infrastructure. This approach enhances scalability and flexibility in managing large-scale storage systems by dynamically adjusting the scope of data collection based on specific update requirements. The invention improves efficiency in distributed storage management by minimizing redundant operations and focusing on the necessary storage units for each configuration update.
13. The processing system of claim 12 , wherein the data collected from the proper subset of the plurality of storage units includes at least one of statistics or logs corresponding to the proper subset of the plurality of storage units.
A processing system is designed to monitor and analyze data from a subset of storage units within a larger storage system. The system collects and processes data such as statistics or logs from this subset of storage units to assess performance, health, or operational status. The collected data may include metrics like read/write speeds, error rates, or usage patterns, which are then analyzed to identify trends, anomalies, or potential failures. This approach allows for targeted monitoring of specific storage units rather than the entire system, improving efficiency and reducing computational overhead. The system may also use the collected data to generate alerts, optimize storage operations, or trigger maintenance actions. By focusing on a proper subset of storage units, the system can provide detailed insights without the need for full-system monitoring, making it suitable for large-scale storage environments where selective monitoring is beneficial. The data collection and analysis processes are automated, ensuring continuous and real-time assessment of the selected storage units.
14. The processing system of claim 11 , wherein the statistics collection parameters further indicate a selected time frame for statistics collection based on the user input.
Technical Summary: This invention relates to a processing system designed to collect and analyze statistics from a network or computing environment. The system addresses the challenge of efficiently gathering and processing statistical data to monitor performance, usage, or other metrics in real-time or over specific time frames. The system includes a user interface that allows users to define and adjust statistics collection parameters, including selecting a specific time frame for data collection. This enables users to focus on relevant time periods for analysis, improving the accuracy and usefulness of the collected data. The system dynamically applies these parameters to filter and process the statistics accordingly, ensuring that the collected data aligns with the user's specified requirements. By allowing customizable time frames, the system enhances flexibility and precision in monitoring and analyzing statistical information.
15. The processing system of claim 11 , further comprising: generating new configuration parameters, wherein the new configuration parameters are based on the aggregated storage statistics; and generating a new configuration update request for transmission to at least one of the plurality of managing units based on the new configuration parameters.
This invention relates to a processing system for managing storage resources in a distributed computing environment. The system addresses the challenge of dynamically optimizing storage performance and efficiency by analyzing aggregated storage statistics and generating configuration updates to managing units. The processing system collects and aggregates storage statistics from multiple storage devices or nodes, which may include metrics such as read/write latency, throughput, capacity utilization, and error rates. These statistics are used to assess the current performance and health of the storage system. Based on the aggregated data, the system generates new configuration parameters designed to improve performance, balance load, or mitigate issues. These parameters may include adjustments to caching policies, data distribution strategies, or resource allocation settings. The system then generates a new configuration update request containing the updated parameters and transmits it to one or more managing units responsible for enforcing the changes. The managing units apply the new configurations to the storage devices, ensuring the system adapts to changing workloads or conditions. This dynamic adjustment process helps maintain optimal storage performance without manual intervention. The invention builds on a prior system that aggregates storage statistics and distributes them to managing units. By adding the ability to generate and apply new configuration parameters based on the aggregated data, the system enables automated, data-driven optimization of storage resources. This approach reduces administrative overhead and improves system responsiveness to performance fluctuations.
16. The processing system of claim 11 , further comprising storing the collected storage unit data in a memory coupled to the DSN monitoring unit, and wherein generating the aggregated storage statistics is further based on a plurality of past collected storage unit data stored in the memory.
A distributed storage network (DSN) monitoring system collects and analyzes storage unit data to generate aggregated statistics for monitoring and managing the network. The system includes a DSN monitoring unit that gathers data from multiple storage units, such as performance metrics, capacity usage, and error rates. This data is stored in a memory coupled to the monitoring unit, allowing historical analysis. The system generates aggregated storage statistics by processing both current and past collected data, enabling trend analysis, predictive maintenance, and performance optimization. By leveraging historical data, the system can identify patterns, detect anomalies, and improve decision-making for storage resource management. The monitoring unit may also include a user interface for displaying the aggregated statistics, facilitating real-time and historical monitoring of the DSN. This approach enhances reliability, efficiency, and scalability in distributed storage environments.
17. The processing system of claim 11 , further comprising generating projected storage data indicating when future storage will be needed based on the collected storage unit data.
A processing system monitors storage units to optimize data management. The system collects data from storage units, including usage metrics, performance metrics, and environmental conditions. This data is analyzed to predict future storage needs, such as when additional storage capacity will be required. The system generates projected storage data, which estimates when storage resources will be depleted or when new storage units should be provisioned. This projection helps in proactive resource allocation, preventing data loss or performance degradation. The system may also include features like automated alerts, capacity planning, and dynamic reallocation of storage resources based on the collected data. By continuously monitoring and analyzing storage conditions, the system ensures efficient use of storage infrastructure while minimizing downtime and operational disruptions. The projected storage data can be used for long-term planning, such as scaling storage capacity or migrating data to different storage tiers. The system is particularly useful in environments with fluctuating storage demands, such as cloud computing, enterprise data centers, or distributed storage networks.
18. A non-transitory computer readable storage medium comprises: at least one memory section that stores operational instructions that, when executed by a processing system of a dispersed storage network (DSN) that includes a processor and a memory, causes the processing system to: receive user input, wherein the user input includes configuration parameters that include statistics collection parameters and wherein the statistics collection parameters indicate a selected plurality of statistics to collect based on the user input; generate a configuration update request for transmission, via a network, to a plurality of managing units based on the configuration parameters, wherein each the plurality of managing units transmit, via the network, a plurality of update specifications to a plurality of storage units managed by the each of the plurality of managing units in response to receiving the configuration update request, wherein the plurality of storage units are separate from the plurality of managing units, and wherein the plurality of managing units apply configuration specifications of the configuration update request to themselves in response to receiving the configuration update request; generate a statistics collection request for transmission, via the network, to the plurality of managing units based on the statistics collection parameters, wherein each the plurality of managing units transmit, via the network, a plurality of statistics collection requests to the plurality of storage units managed by the each of the plurality of managing units in response to receiving the statistics collection request; receive, in response to the statistics collection request, collected storage unit data from each of the plurality of managing units that includes data collected by the each of the plurality of managing units, via the network, from the plurality of storage units managed by the each of the plurality of managing units, wherein the collected storage unit data received from each of the plurality of managing units corresponds to the selected plurality of statistics of the statistics collection parameters of the user input; and generate aggregated storage statistics based on the collected storage unit data received from each of the plurality of managing units.
A system for managing and collecting statistics in a dispersed storage network (DSN) involves a computer-readable storage medium storing instructions that, when executed, enable a processing system to receive user input specifying configuration parameters, including statistics collection parameters that define which statistics to gather. The system generates a configuration update request transmitted to multiple managing units within the DSN. Each managing unit applies the configuration specifications to itself and forwards update specifications to its associated storage units, which are separate from the managing units. The system also generates a statistics collection request sent to the managing units, which then relay statistics collection requests to their respective storage units. The managing units collect data from the storage units based on the specified statistics and return the aggregated data to the processing system. The system then generates comprehensive storage statistics by combining the collected data from all managing units. This approach allows centralized monitoring and analysis of distributed storage performance metrics in a DSN.
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August 20, 2019
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